The present invention generally relates to vehicle maintenance needs alert and related vehicle information management methods and systems. The present invention also relates to real-time monitoring and data analysis of in-vehicle devices and sensors in a fleet of numerous commercial vehicles from a remote location via wireless communications. Furthermore, the present invention also relates to machine-based automatic determination of correlating patterns between a previously-identified vehicle maintenance need and a subsequent vehicle breakdown.
In commercial transport fleet operations, it is common to accumulate hundreds of thousands of miles in many of the commercially-operated vehicles (e.g. taxis, buses, trucks) annually. The conventional method of tracking of each commercial vehicle's maintenance needs in a typical commercial fleet operation merely involves periodic mechanic checkups and parts and fluid replacements. In many cases, essential or desirable vehicle maintenance and part/fluid replacements are delayed or unperformed due to negligence or incompetence arising from the complexity of tracking maintenance timing and records manually by commercial vehicle drivers and operators.
Furthermore, with conventional vehicle maintenance practice, it is also difficult to identify, track, and respond to vehicle-specific problems and potential parts failures until a particular vehicle suffers an outright mechanical breakdown that results in operational downtime. Conventional computer database systems have been utilized to accommodate manually-set maintenance reminders and to store vehicle maintenance records electronically, but these conventional systems merely track static information manually entered by a human operator, and are unable to provide proactive and intelligent machine sensor-based assessment of dynamically-changing maintenance needs or conditions of individual vehicles in a commercial fleet operation.
Therefore, it may be desirable to devise a novel commercial fleet maintenance alert system that performs automated and intelligent analysis of each vehicle's OBD and other sensor output parameters in real time from a remote monitoring station to determine and alert each fleet vehicle's maintenance needs to a driver or a commercial fleet operator.
Furthermore, it may also be desirable to devise a novel commercial fleet maintenance alert system that provides a machine-level pattern analysis that correlates a previously-alerted maintenance need of a particular vehicle with a subsequent breakdown of the particular vehicle in a commercial fleet to predict a future probability of similar breakdowns by other vehicles in the commercial fleet.
In addition, it may also be desirable to devise a method of operating such novel commercial fleet maintenance alert systems for commercial vehicle operation managers and commercial vehicle drivers.